Panorama is the process of combining multiple photographic images with overlapping fields of view to produce a high-resolution image. In the ideal input image capture for panorama scene generation, all of the images share the same center of projection (see FIG. 1), and hence there is no parallax error when the images are registered across, warped and stitched together. But with hand held cameras, it is highly difficult to make sure there is a common center of projection for all the images due to the unstable hand holding the camera. It is also more convenient for a user to capture images with some amount of image translation apart from rotation. That is, input images with small amounts of translation end up with different centers of projection. The output panorama image suffers from errors due to parallax between captured images.
One solution would minimize the problem of errors caused due to parallax in panorama generation, perhaps by intelligently identifying the input images with the same or similar center of projection (even when they are captured by handheld cameras). This may be accomplished with the use of light field camera image capture. A light field (LF) camera, also called a plenoptic camera, is a camera that can capture 4-dimensional (4D) light field information about a scene. For minimal mis-registration in the final output, the center of projection of all of the individual images needs to be same or as close as possible, otherwise the parallax error in the captured individual images will show up as mis-registration in the final output.
In the case of captured images from LF cameras, for each captured image one can obtain multiple view angled images which have different centers of projection. In that instance, a method is needed to identify and select the views from each of the images with the same or closely related center of projection by which one can produce the parallax error-minimized/free panoramas.